dataset_seed.txt

# This file contains seed data for training the bigram model.
# Add more DSL lines and code snippets to improve the model's
# suggestions.

# To expand this file safely:
# 1. Do not include any proprietary data.
# 2. Use generic or generated examples.
# 3. Keep the lines short and focused.
# 4. Aim for variety in syntax and keywords.

# Common programming patterns
if condition then statement
if condition then { statement1 statement2 }
for item in collection do process(item)
while condition do update state
try { operation } catch { handle error }
function name(parameters) { body }
class name { members }
return value
print message
log event
assert condition
throw exception

# Generic DSL-like commands
create object type="widget" name="myWidget"
update property object="myWidget" property="color" value="blue"
delete object type="widget" name="myWidget"
get data source="database" table="users"
set setting name="timeout" value="30"
call service method="calculate" parameters="x, y"
send message destination="queue" content="data"
receive message source="queue"
validate input type="string" pattern="[a-zA-Z]+"
transform data source="input" destination="output" rule="uppercase"
execute command name="deploy" target="server"
schedule task time="10:00" command="backup"
monitor resource type="CPU" threshold="80%"
notify event type="error" recipient="admin"

# Code snippets (C-like syntax)
int x = 0;
string message = "Hello, world!";
if (x > 0) { print("Positive"); } else { print("Non-positive"); }
for (int i = 0; i < 10; i++) { print(i); }
while (running) { updateState(); }
try { doSomething(); } catch (Exception e) { handleError(e); }
public class MyClass { public int value; }
return result;
print("Operation completed");
log("User logged in");
assert(value > 0);
throw new Exception("Invalid input");

# More diverse DSL examples
define workflow name="processData" steps="get, transform, validate, send"
map variable="x" expression="y + z"
reduce list operation="sum"
filter list condition="value > 10"
sort list field="name" order="ascending"
group list field="category"
join table1 table2 on key
pivot table column="date" value="sales"
unpivot table column="attribute" value="value"

# More examples - DSL control flow:
if ( condition ) { action ; }
else { alternative_action ; }

# More examples - Looping constructs:
foreach ( item in collection ) { process( item ) ; }
while ( condition ) { update_state ; }

# More examples - Data structures:
list = [ item1 , item2 , item3 ] ;
dictionary = { key1 : value1 , key2 : value2 } ;

# More examples - Error handling:
try { risky_operation ; } catch ( exception_type exception_name ) { handle_exception ; }

# More examples - Functional programming style:
map ( collection , transform_function ) ;
filter ( collection , predicate_function ) ;
reduce ( collection , accumulator_function , initial_value ) ;

#More examples - REST API-like DSL:
GET /resource/id
POST /resource data={ field1 : value1 , field2 : value2 }
PUT /resource/id data={ field1 : new_value1 }
DELETE /resource/id

#More examples - SQL-like DSL:
SELECT field1 , field2 FROM table WHERE condition
INSERT INTO table ( field1 , field2 ) VALUES ( value1 , value2 )
UPDATE table SET field1 = new_value1 WHERE condition
DELETE FROM table WHERE condition